Data combination method in Remote Sensing tasks in case of conflicting information sources

S. Alpert
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Abstract

Nowadays technologies of UAV-based Remote Sensing are used in different areas, such as: ecological monitoring, agriculture tasks, exploring for minerals, oil and gas, forest monitoring and warfare. Drones provide information more rapidly than piloted aerial vehicles and give images of a very high resolution, sufficiently low cost and high precision.Let’s note, that processing of conflicting information is the most important task in remote sensing. Dempster’s rule of data combination is widely used in solution of different remote sensing tasks, because it can processes incomplete and vague information. However, Dempster’s rule has some disadvantage, it can not deal with highly conflicted data. This rule of data combination yields wrong results, when bodies of evidence highly conflict with each other. That’s why it was proposed a data combination method in UAV-based Remote Sensing. This method has several important advantages: simple calculation and high accuracy. In this paper data combination method based on application of Jaccard coefficient and Dempster’s rule of combination is proposed. The described method can deal with conflicting sources of information. This data combination method based on application of evidence theory and Jaccard coefficient takes into consideration the associative relationship of the evidences and can efficiently handle highly conflicting sources of data (spectral bands).The frequency approach to determine basic probability assignment and formula to determine Jaccard coefficient are described in this paper too. Jaccard coefficient is defined as the size of the intersection divided by the size of the union of the sample sets. Jaccard coefficient measures similarity between finite sets. Some numerical examples of calculation of Jaccard coefficient and basic probability assignments are considered in this work too.This data combination method based on application of Jaccard coefficient and Dempster’s rule of combination can be applied in exploring for minerals, different agricultural, practical and ecological tasks.
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信息源冲突情况下遥感任务数据组合方法
如今,基于无人机的遥感技术被应用于不同的领域,如:生态监测、农业任务、矿产勘探、石油和天然气、森林监测和战争。无人机提供信息的速度比有人驾驶的飞行器更快,提供的图像分辨率非常高,成本低,精度高。让我们注意到,在遥感中,处理相互矛盾的信息是最重要的任务。Dempster数据组合规则由于可以处理不完整和模糊的信息,被广泛应用于不同遥感任务的求解中。然而,Dempster规则也有一些缺点,它不能处理高度冲突的数据。当大量证据彼此高度冲突时,这种数据组合规则会产生错误的结果。为此,提出了一种基于无人机的遥感数据组合方法。该方法具有计算简单、精度高的优点。本文提出了一种基于Jaccard系数和Dempster组合规则的数据组合方法。所描述的方法可以处理冲突的信息源。这种基于证据理论和Jaccard系数的数据组合方法考虑了证据之间的关联关系,能够有效地处理高度冲突的数据源(谱带)。本文还介绍了确定基本概率分配的频率法和确定雅卡德系数的公式。Jaccard系数定义为交集的大小除以样本集的并集的大小。雅卡德系数度量有限集之间的相似性。本文还考虑了一些计算雅卡德系数和基本概率赋值的数值例子。这种基于Jaccard系数和Dempster组合规则的数据组合方法可应用于矿产勘探、各种农业、实用和生态任务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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